Effortless awareness: using real time neurofeedback to investigate correlates of posterior cingulate cortex activity in meditators' self-report.

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HUMAN NEUROSCIENCE

ORIGINAL RESEARCH ARTICLE

published: 06 August 2013
doi: 10.3389/fnhum.2013.00440

Effortless awareness: using real time neurofeedback to
investigate correlates of posterior cingulate cortex activity
in meditators' self-report

Kathleen A. Garrison 1 , Juan F. Santoyo 2 , Jake H. Davis 2 - 3 , Thomas A. Thornhill IV 1 , Catherine E. Kerr 4
and Judson A. Brewer 1 *

' Yale Therapeutic Neuroscience Clinic, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA

2 Contemplative Studies Initiative, Clinical and Affective Neuroscience Laboratory, Department of Neuroscience, Brown University, Providence, Rl, USA

3 Department of Philosophy and Cognitive Science, City University of New York Graduate Center, New York, NY USA

4 Department of Family Medicine, Brown University, Providence, Rl, USA

Edited by:

Wendy Hasenkamp, Mind and Life
Institute, USA

Reviewed by:

Giuseppe Pagnoni, University of
Modena and Reggio Emilia, Italy
Jean-Philippe Lachaux, Institut
National de la Sante et de la
Recherche Medicale, France

*Correspondence:

Judson A. Brewer, Yale Therapeutic
Neuroscience Clinic, Department of
Psychiatry, Yale University School of
Medicine, 300 George St. Suite 901,
New Haven, CT 06511, USA
e-mail: judson.brewer@yale.edu

Neurophenomenological studies seek to utilize first-person self-report to elucidate
cognitive processes related to physiological data. Grounded theory offers an approach
to the qualitative analysis of self-report, whereby theoretical constructs are derived
from empirical data. Here we used grounded theory methodology (GTM) to assess
how the first-person experience of meditation relates to neural activity in a core
region of the default mode network — the posterior cingulate cortex (PCC). We analyzed
first-person data consisting of meditators' accounts of their subjective experience during
runs of a real time fMRI neurofeedback study of meditation, and third-person data
consisting of corresponding feedback graphs of PCC activity during the same runs.
We found that for meditators, the subjective experiences of "undistracted awareness"
such as "concentration" and "observing sensory experience," and "effortless doing"
such as "observing sensory experience," "not efforting," and "contentment," correspond
with PCC deactivation. Further, the subjective experiences of "distracted awareness"
such as "distraction" and "interpreting," and "controlling" such as "efforting" and
"discontentment," correspond with PCC activation. Moreover, we derived several novel
hypotheses about how specific qualities of cognitive processes during meditation relate
to PCC activity, such as the difference between meditation and "trying to meditate."
These findings offer novel insights into the relationship between meditation and mind
wandering or self-related thinking and neural activity in the default mode network, driven
by first-person reports.

Keywords: neurophenomenology, grounded theory, real time fMRI, meditation, posterior cingulate cortex, self-
report, introspection, self-referential processing

INTRODUCTION

First-person subjective experience is critical for furthering our
understanding of cognitive processes. Recent interest surrounds
neurophenomenology — an approach that utilizes introspective
self-report to inform the analysis and interpretation of objec-
tive physiological data related to consciousness and cognition
(Varela, 1996; Lutz and Thompson, 2003). For functional neu-
roimaging studies, first-person reports of experience can be used
to reduce the opacity of both the neural response and cognitive
task strategy.

We recently conducted a real time functional MRI (rtfMRI)
study of meditation to closely link the subjective experience of
meditation with neuroimaging data in real time (Garrison et al.,
2013). Adept meditators reported a significant correspondence
between their moment-to-moment experience of meditation and
real time neurofeedback from the posterior cingulate cortex
(PCC), a brain region previously found to be activated during
self-related thinking (Buckner et al., 2008) and deactivated dur-
ing meditation (Brewer et al., 2011). Moreover, they were able to

use what they had learned about the subjective qualities of med-
itation that related to feedback in order to volitionally deactivate
the PCC. However, because the PCC has been associated with
numerous cognitive states (Andrews-Hanna et al., 2010) the spe-
cific aspects of subjective experience that relate to PCC activity are
yet unknown.

Here we use grounded theory methodology (GTM; Glaser and
Strauss, 1967) to induce theory grounded in first-person data,
consisting of meditators accounts of their experience during runs
of the rtfMRI study, and third-person data, consisting of corre-
sponding feedback graphs representing PCC activity during the
same runs. GTM is a method of qualitative inquiry that seeks to
generate theory from empirical data. Developed for use in soci-
ology, GTM is now widely used across disciplines (e.g., Kennedy
and Lingard, 2006), including the analysis of meditation diaries
in clinical trials of Mindfulness Based Stress Reduction (e.g., Kerr
et al., 2011). Here we use GTM to describe and quantify phe-
nomenal subjective experience related to meditation. Specifically,
the purpose of the current study was to investigate the subjective

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Garrison et al.

Neurophenomenology of meditation using neurofeedback

experience of meditation corresponding to PCC activity in adept
meditators, in order to derive testable hypotheses for further
inquiry.

MATERIALS AND METHODS
PARTICIPANTS

Ten experienced meditators participated in the study (7 male,
3 female; 9 right-handed, 1 ambidextrous; 9 White, non-
Hispanic, 1 Hispanic; mean age 49.2 ± 12.5 years; mean
education 19.2 ± 3.0 years). Meditators were experienced
in different contemplative traditions including Theravada
(N = 4), Zen (N = 3), Catholic Contemplative (N = 1),
Catholic Contemplative and Zen (N = 1), and Gelugpa of
Tibetan Buddhism (N = 1); and on average reported a total of
10, 567 ± 4276 practice hours over 18.4 ± 4.9 years, comprised
of daily practice and retreats. All participants provided informed
consent for the study in accordance with institutional guidelines.

REAL TIME fMRI ACQUISITION

We used a Siemens 1.5 Tesla Sonata MRI with standard eight-
channel head coil to acquire a high-resolution anatomical scan,
collected using a magnetization prepared rapid gradient echo
(MPRAGE) sequence (TR/TE = 2530/3. 34ms, 160 contiguous
sagittal slices, slice thickness 1.2 mm, matrix size 192 x 192,
flip angle = 8°), and used to register data to the Montreal
Neurological Institute (MNI) template brain (Mazziotta et al,
1995), which was used to define the overall reference coordi-
nate system. Next a lower resolution T 1 - weighted anatomical scan
was acquired (TR/TE = 500/11 ms, field ofview= 220mm, slice
thickness = 4 mm, gap = 1 mm, 25 AC-PC aligned axial-oblique
slices). An initial functional reference scan was acquired to regis-
ter the PCC region of interest from MNI space. The PCC region
of interest was defined based on peak deactivation in our previ-
ous study of meditation (MNI coordinates: —6, —60, 18) (Brewer
et al, 2011). Functional images for feedback runs were then
acquired beginning in the same slice location as the Tl -weighted
data, using a T2* -weighted gradient- recalled single shot echo-
planar pulse sequence {TR/TE = 2000/35 ms, flip angle = 90°,
bandwidth = 1446 Hz/pixel, matrix size = 64 x 64, field of view
= 220 mm, voxel size = 3.5 mm, interleaved, 46 volumes), with
the last volume discarded.

REAL TIME fMRI DISPLAY

We used E-prime 1.2 (pstnet.com) to display a feedback graph
representing the percent blood oxygenation level-dependent
(BOLD) signal change in the PCC (corrected for global brain sig-
nal) during meditation relative to baseline (see Figures 4, 5 for
examples). Real time image processing and feedback display for
this study have been previously reported (Garrison et al, 2013).
We note that image processing, from acquisition to feedback
display, required less than 1 s.

REAL TIME fMRI PROTOCOL

Our rtfMRI protocol was designed to allow meditators to "dis-
cover" how a feedback graph representing activity in the PCC
corresponded with their own subjective experience of medita-
tion in real time. This protocol was comprised of a 4-step series

of runs progressing from: (1) meditation with offline feedback
(feedback graph shown offline after each run); (2) meditation on
a graph with offline feedback; (3) meditation with real time feed-
back from the PCC; to (4) volitional manipulation of the feedback
graph. This protocol was designed to progress from the most nat-
uralistic setting for meditation (step 1, 4 runs), to meditation
using a dynamic graph as the object of focus (step 2, 3 runs),
to meditation with a graph of feedback from one's own brain in
real time (step 3, 3 runs), to volitional manipulation of the feed-
back graph (step 4, 6 runs). Each run began with a 30 s baseline
task, during which participants viewed adjectives and were asked
to "think about and decide" if the words described them (Kelley
et al, 2002). Similar tasks requiring evaluation of trait adjectives
have been shown previously to engage self- related processing and
regions of the default mode network including the PCC (Northoff
et al., 2006). Here the active baseline task was used to provide
a more stable baseline between groups, as we have previously
found differences in PCC activity between meditators and non-
meditators at rest (Brewer et al., 2011), and to provide a more
stable baseline across runs within-subjects. Baseline was followed
by a 1-min meditation task, with specific additional instructions
per step, as described below.

REAL TIME fMRI INSTRUCTIONS

Meditation with offline feedback

For the first meditation task, after the word task, the screen will
go blank. This will be your cue to meditate for about 60 s. During
the meditation, please pay attention to the physical sensation of
the breath wherever you feel it most strongly in the body. Follow
the natural and spontaneous movement of the breath, not trying
to change it in any way. Just pay attention to it. If you find that
your attention has wandered to something else, gently but firmly
bring it back to the physical sensation of the breath. Please keep
your eyes open.

Meditation on a graph with offline feedback

For the second meditation task, after the word task, you will see
a graph start to form, that will fill in a new line every 2 s. This
is an arbitrary graph, and does not show your brain activity. We
ask that when you see the graph start to form, you again meditate
for 60 s, here using the graph as your object of meditation — just
paying attention to the graph as you would any other object of
focus or concentration such as your breath. Pay attention to the
graph, not trying to change it in any way. If you find that your
attention has wandered to something else, gently but firmly bring
it back to the graph. Please keep your eyes open.

Meditation with real time feedback

For the third meditation task, after the word task, you will see a
similar graph start to form, and again we ask that you meditate for
60 s, using the graph as your object of meditation. Now the graph
you see during the run will show relative activity in a particular
region of your brain. Thus, for these runs, the graph you see dur-
ing the run may correspond with your experience. There is a 2-4 s
delay between your brain activity and the graph, thus if the graph
does correspond with your experience, it will do so with a delay
of 2^4 s. It may be helpful to look back at short stretches of time

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Neurophenomenology of meditation using neurofeedback

to notice your experience in relation to how the graph changes.
We ask that you meditate, using the graph as your object of medi-
tation, and now also notice your moment-to-moment experience
in relation to how the graph changes.

Volitional manipulation of the feedback graph

Participants were first asked to volitionally decrease the feedback
graph for 3 runs, using the following instructions: For the final
task, after the word task, you will see a similar graph start to form
that will show relative activity in a particular region of your brain,
and may correspond with your experience. For these runs, we
will ask you to use your mind to make the graph go blue. You
may draw from your experience over the previous runs. You will
have 60 s.

Participants were then asked to volitionally increase the feed-
back graph, using the following instructions: Finally, for 3 runs
we will ask you to use your mind to make the graph go red. You
may draw from your prior experience, and you'll have 60 s.

SELF-REPORT

For steps 1, 2, after each run, meditators were first asked: (1)
Please briefly describe your experience during the meditation.
They were then shown a graph of their brain activity during
the meditation (offline feedback) and asked: (2) On a scale
from 0-10, how well does the graph correspond with your experi-
ence during the meditation, 0 being not at all, 10 being perfectly?
and (3) How did you know? For step 3, after each run, medita-
tors were asked the same questions, however, for these runs, they
were asked to rate how well the graph they saw during the run
(real time feedback) corresponded with their experience. For step
4, after each run, meditators were asked the same questions, and
also to report: (4) What strategy did you use to make the graph go
blue/red? Self-reports were audio recorded for offline transcrip-
tion. Self-report for questions 1-4 were included in the current
analysis.

Meditators practiced self-report for each step prior to actual
scanning. Overall, they were instructed: In all of the meditation
tasks, we are interested in your own experience of meditation,
paying attention to an object of focus or concentration. After each
run, we'll ask you to describe your own experience during the
meditation period. In this study, we're interested in how activ-
ity in particular brain regions lines up with your experience of
meditation. For (1) Please briefly describe your experience dur-
ing the meditation, they were instructed: This question is open
ended, but it's important to be concise, giving us the highlights
of your experience during the meditation. For example, we may
ask, "Was there anything different in your experience between the
beginning, middle, and end of the meditation?" For (2) On a scale
from 0-10, how well does the graph correspond with your expe-
rience during the meditation, they were instructed: The graph
shows relative activity in a particular region of your brain over
the meditation period. This graph may correspond with your
moment-to-moment experience during the meditation. To make
it easy to follow, values above the line will be red, and values below
the line will be blue. We will ask you to look at the graph, and to
consider how the graph does or does not correspond with your
experience during the meditation. For example, we'll ask you to

consider how the graph corresponds with your general experience
of meditation, including mental effort, concentration, or mental
state. Don't worry about every little detail, instead focusing on
the more general aspects of these. For example, if you remem-
ber something about your experience at the beginning, middle or
end of the meditation, you may look to see if your experience is
reflected in how the graph changes. Any time you are shown a
graph of your brain activity, the graph will show relative activity
in a single brain region. We are only using one brain region for
this study. For (3) How did you know, they were instructed: In
other words, what about the graph does or does not correspond
with your experience? Was there anything different in your expe-
rience that you notice corresponds to how the graph changes? We
may refer to a specific aspect of the graph and ask "Did anything
in particular correspond to this point on the graph?"

Meditators were asked five additional Likert item ques-
tions after each run. These ratings data are reported elsewhere
(Garrison et al, 2013), but the questions are described here
because they have the potential to influence meditators' self-
reports. Questions included: (1) On a scale of 0-10, how dis-
tracted or focused were you during the meditation (0 = very
distracted, 10 = very focused)? (2) On a scale of 0-10, how aware
were you during the meditation (0 = not aware, 10 = very aware)?
For this question, they were instructed: How aware were you of
whatever arose in your moment to moment awareness? For exam-
ple, you can be very aware that you are distracted. (3) On a scale
of 0-10, how vivid was your experience (0 = not vivid, dull, hazy,
fuzzy, 10 = vivid, sharp, clear, crisp)? (4) On a scale of —10 to
10, how was your mental state (— 10 = sluggish or drowsy, 0 =
relaxed but balanced, steady, even, alert, and 10 = agitated, racing,
excited or restless)? (5) On a scale of 0-10, how was your mental
effort (0 = effortless 10 = forced, pushed, tight, contracted)?

DATA ANALYSIS

Self- reports were transcribed verbatim by research assistants. The
data consisted of these transcripts for each run and correspond-
ing figures of feedback graphs of PCC activity from the same
run. Qualitative data analysis was conducted following the princi-
ples of grounded theory (Glaser and Strauss, 1967), which entails
an iterative process of data coding and analysis, outlined below.
The goal of data analysis was to evaluate how self-reported expe-
rience corresponds with PCC activation or deactivation during
meditation in experienced meditators.

Initial or open coding is used to identify and label words or
phrases in the data (Birks and Mills, 2011). In our study, at the
level of initial coding, data were analyzed as sets of self-report
transcripts and graphs of PCC activity from the same run, in
order to generate specific hypotheses about the relation between
subjective experience and PCC activity. Initial coding involved
reading each line of text while referring to the graph of PCC activ-
ity, and recording all instances of reference to the graph, either
explicit (e.g., "the graph was blue") or implicit (e.g., across time,
"near the end of the run"), in order to capture meaning between
the datasets at those instances. Both the first-person self-report
data and the third-person brain imaging data were required to
indicate PCC activation or deactivation for the initial code to be
categorized as such. Excerpts were taken from the text, coded into

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Neurophenomenology of meditation using neurofeedback

a database, and labeled according to whether they corresponded
with PCC activation or deactivation, as well as their specific con-
tent of meaning. For example, the excerpt "I noticed my breath
and then my body somewhat, and then it started to go more
blue" was labeled as "PCC deactivation," "noticing the breath,"
and "noticing the body." In this way, initial coding was used
to generate ideas by open coding many instances in the dataset
(Figure 1).

Focused coding is used to group codes into conceptual cat-
egories as higher order codes (Birks and Mills, 2011). Focused
coding employs a constant comparative method, whereby data
are compared with emerging codes to identify patterns, revise
terminology, combine, add, or eliminate codes, based on their
prevalence, conceived importance, and relevance. For example,
"noticing the breath" and "noticing the body" were combined
into the open code "physical sensations" and sorted under the
central code "focus."

Theoretical sampling refers to resampling the data to return
codes that only fit in existing categories (Birks and Mills, 2011).
Datasets were resampled to ensure that emergent codes fit with
the content of meaning of all of the relevant text excerpts
under those codes. The aim is to ensure that the final the-
oretical codes are saturated in the data, so that any further
analysis results in no new ideas or codes. At this stage we also
recorded the frequency with which a given theoretical code was
grounded in the data, i.e., the number of instances of self-
report excerpts used to derive the coding structure leading to
that theoretical code. Finally, we grouped theoretical codes into
principal constructs that corresponded with PCC activation or
deactivation.

All runs of the step-wise rtfMPJ protocol were included in
the analysis. However, the protocol was designed such that across
steps, meditators could "discover" how their own experience of
meditation corresponded to the feedback graph. This process
involved getting used to meditating in the fMPJ scanner (step 1),
meditating while viewing a mock feedback graph (step 2), med-
itating while seeing a feedback graph from their own brain
(step 3), and finally, volitionally manipulating the feedback graph
(step 4). As expected, this learning process was represented in
the self-report data, such that meditators reported more instances
of getting used to the experimental paradigm in earlier runs
(e.g., "It took a moment to adjust to the sound and the looking,
hut as it progressed I felt more comfortable doing it"). As such,
though all runs of the stepwise protocol were included in open
coding, the final stages of theoretical sampling focused on latter
steps (steps 3, 4).

GTM was conducted by the second author (Juan F. Santoyo),
a 21 -year old Hispanic male undergraduate Neuroscience and
Contemplative Science student, with no other role in the study.
Prior to GTM, Juan F. Santoyo disclosed limited familiarity with
literature related to the PCC (including Brewer et al., 2011) but
no preconceived notion of PCC function; and a personal medita-
tion practice (including Mahayana, Theravada, Mahasi, classical
Daoist, and mindfulness), which provided him a bias through
which to directly interpret the self-report data on introspection
(as suggested by Wallace, 2000). As part of GTM, he composed
memos of the coding process and emergent ideas, to both stim-
ulate and provide a record of the coding process, and to allow
for regular second-person cross-checking of emergent ideas with
co-authors. This allowed for independent evaluation of the qual-
itative analysis. GTM is generally carried out by an individual
researcher, with explicit acknowledgment of the role of the indi-
vidual in generating hypotheses from the data (Mills et al., 2006).
Hypotheses are derived from the data using an iterative process
of coding and memo writing, with coding strategies, the emer-
gent coding framework, and interpretation of data cross-checked
by co-authors. In this way, elements of multiple coding provide
cross-checking of grounded theory without multiple coding of
the dataset (Barbour, 2001).

RESULTS

The open codes, central codes, and theoretical codes derived from
the data using GTM are displayed in Figure 1. From these, we
determined principal constructs for the phenomena of subjective
experience that corresponded with PCC deactivation (Figure 2)
or PCC activation (Figure 3). Specific examples of data ground-
ing the principal constructs are provided in Figures 4, 5.

"UNDISTRACTED AWARENESS" AND "EFFORTLESS DOING" AS BASIC
ELICITING FACTORS OF PCC DEACTIVATION

Meditators reported phenomena in their subjective experience
related to "undistracted awareness" or "effortless doing" as basic
eliciting factors of PCC deactivation (Figure 2).

"Undistracted awareness" emerged from data related to set-
tled, concentrated, or clear attention to momentary experience,
and is comprised of the theoretical codes for "concentration" and
"observing sensory experience" (Figure 4). For "concentration"

Open Codes

Open awareness

Not "efforting"

Tranquility

Focus on the body

Focus on the nostrils

Focus on the graph

Focus on sensations
Focus on visual input

Thinking about work

Remembering

Thinking about a place
Thinking about an object

Interpreting the task

Interpreting the graph

Interpreting experience

Searching

Central Codes

Not "efforting"

Pleasure
Equanimity

Clarity

Physical sensations

Mental objects

Auditory objects

Deliberating

Remembering

Self-related thinking

"Efforting"

Theoretical
Codes

Not "efforting"

| Observing sensory experience

Engaging with .

Discontentment

"Efforting"

FIGURE 1 | Representation of the open codes, central codes, and
theoretical codes derived from self-report and neurofeedback graph
data using grounded theory methodology.

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Neurophenomenology of meditation using neurofeedback

Deactivation

Undistracted
Awareness

Effortless
Doing

Concentration

n = 99

Observing Sensory
Experience

Not "efforting"

n = 48

Contentment

n = 28

FIGURE 2 | Phenomena of the subjective experience of meditation related to posterior cingulate cortex deactivation (n = number of occurrences in
self-reports).

. . , , Self-related - ... . . . Physical Visual Auditory Mental

Muddled thinking Dellberatm g Memorles sensations objects objects objects | Dlspleasure

FIGURE 3 | Phenomena aspects of the subjective experience of meditation related to posterior cingulate cortex activation (n = number of
occurrences in self-reports).

meditators reported instances of single-pointed concentration
such as focus on the breath (i.e., concentration on the task) or
open focus marked by a quality of clarity (n = 99 instances).
For "observing sensory experience" in the context of "undis-
tracted awareness," meditators reported instances of noticing
sensory stimulus-such as visual stimulus, physical sensations, or
thoughts — but not being distracted by their sensory experience
(n = 76).

"Effortless doing" emerged from data related to a calm, tran-
quil, relaxed, and effortless way of doing things, and is comprised
of the theoretical codes for "observing sensory experience," "not
efforting," and "contentment" (Figure 4). For "observing sen-
sory experience" in the context of "effortless doing," meditators
reported instances of paying attention to sensory stimulus but not
engaging with their sensory experience by deliberative thinking
or action (n = 76 total). For "not efforting" meditators reported
instances of relaxation without effort and without any attempt to
control their experience, such as when they would just "let go"
and meditate without trying to make anything happen (n = 48).
For "contentment," meditators reported instances of satisfaction
or acceptance of things as they are, feelings of ease, equanimity, or
bliss in = 28).

"DISTRACTED AWARENESS" AND "CONTROLLING" AS BASIC
ELICITING FACTORS OF PCC ACTIVATION

Meditators reported phenomena in their subjective experience
related to "distracted awareness" or "controlling" as basic eliciting
factors of PCC activation (Figure 3).

"Distracted awareness" emerged from data related to distrac-
tion, lack of concentration, or unsettled awareness, such as the
awareness that one's mind is wandering or thinking and that
one is unable to control these processes (i.e., carried away in
thoughts or experience), and is comprised of the theoretical codes
for "distraction" and "interpreting" (Figure 5). For "distraction,"
meditators reported instances of distraction or lack of focus, such
as when they were unable to pay attention during the run or when
they reported feeling hazy, unclear, or muddled (n = 64). For
"interpreting," meditators reported instances of thinking, delib-
erating, or remembering, such as trying to understand the graph
or rehearsing self-report (« = 56).

"Controlling" emerged from data related to trying to change
the way things are or affect experience, often associated with a
dissatisfaction with current experience, and is comprised of the
theoretical codes for "efforting" and "discontentment" (Figure 5).
For "efforting," meditators reported instances of exerting effort

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Neurophenomenology of meditation using neurofeedback

PCC Deactivation
Undistracted Awareness
Concentration Observing sensory experience

(n = 99) (n = 76)

"Very smooth. It was very easy to
concentrate, or a concentrated
meditation this time. ..the blue part"

". . ./ started observing how my mind
was doing, and then it immediately
went back into blue..."

Observing sensory experience

w

Effortless Doing
Not 'efforting'
(n = 48)

"Toward the middle I had some "I noticed ...that the\

thoughts which I don't see on more I relaxed and

the graph maybe because I let stopped trying to do

them kind of flow by" anything, the bluer it went"

Contentment
(n = 28)

V

"I was setting the intention to
cultivate equanimity... when I
set that intention, the blue
spiked downward"

FIGURE 4 | "Undistracted awareness" and "effortless doing" as basic
eliciting factors of posterior cingulate cortex deactivation. Examples of
self-report transcripts and feedback graphs for the theoretical codes leading
to the basic eliciting factors of "undistracted awareness" (top) and
"effortless doing" (bottom).

PCC Activation
Distracted Awareness

Distraction
(n = 64)

Interpreting
(n = 56)

Jl

I

I

"I'm associating ...the red with

sort of the... the intrusion of thought"

"...I was like, 'Whoa that is a lot of red' and
then I noticed my mind was going 'Whoa that
is a lot of red' and I got a little bit caught up in
how I was going to explain that to you"

Controlling

Efforting
(n = 19)

T

Discontentment
fn-MJ

"/ worried that I wasn't using the graph as an
object of meditation, so I tried, like, to look at
it harder or somehow pay attention more to it"

7 brought up memories ofuh,
embarrassment, regret, urn,
interpersonal unskillfulness"

FIGURE 5 | "Distracted awareness" and "controlling" as basic eliciting
factors of posterior cingulate cortex activation. Examples of self-report
transcripts and feedback graphs for the theoretical codes leading to the
basic eliciting factors of "distracted awareness" (top) and "controlling"
(bottom).

in order to make something happen or change one's experience,
such as trying to pay attention or trying to change the graph
(n = 19). For "discontentment," meditators reported instances of
feeling unhappy, uncomfortable, or in some way dissatisfied or

displeased, such as feeling unpleasant emotions such as anger,
wanting the experiment to end, or feeling frustrated with the
feedback graph (n = 14).

DISCUSSION

In this study, we used GTM to analyze self-reports of experi-
ence and graphs of real time neurofeedback in order to evaluate
the phenomena of subjective experience that corresponds with
PCC activity for experienced meditators. We used GTM to derive
testable hypotheses about the relationship between subjective
experience and PCC activity that are grounded in the data. We
found that for meditators, the principle constructs of "undis-
tracted awareness" and "effortless doing" corresponded with PCC
deactivation, whereas "distracted awareness" and "controlling"
corresponded with PCC activation.

These findings are consistent with prior work indi-
cating that the PCC is activated during mind wandering
(Mason et al, 2007) and self-referential processing (Whitfield-
Gabrieli et al, 2011) such as past and future thinking
(Andrews-Hanna et al, 2010), and deactivated during three
meditation practices (concentration, loving kindness, and
choiceless awareness) in expert compared to novice meditators
(Brewer et al., 2011; Pagnoni, 2012). Our primary constructs
for the basic eliciting factors of PCC activity fit well with these
prior findings of PCC activation related to mind wandering
and PCC deactivation related to meditation. From the data,
subjective reports of "distracted awareness" corresponding with
PCC activation included instances of thinking about the past
or future (e.g., "7 began by thinking about a variety of things
that need to be done, emails that need to be sent, things that I
have not done in a timely fashion, that type of thing") and mind
wandering (e.g., "I got caught up in thinking what I was going to
tell you"). Likewise, subjective reports of "undistracted aware-
ness" corresponding with PCC deactivation included instances
of concentration meditation (e.g., "I felt much more focused on
my breath and felt like I had fewer moments of distraction or
interruption").

Beyond confirming previous studies, we demonstrate that
rtfMRI with self-report can be used to generate new data-
driven and testable neurophenomenological hypotheses about
particular brain regions; in this case the PCC. rtfMRI neu-
rofeedback improves the temporal resolution and specificity
between subjective experience and brain activity, as many cog-
nitive processes may be present at any one moment. The
GTM approach is distinct from other neurophenomenology
studies in which for example subjects are provided with
intensive training on how to self-report (e.g., Lutz et al.,
2002). Below we discuss three emergent hypotheses that best
exemplify the strengths of the method, the potential impli-
cations, and the need for further neurophenomenological
investigation.

One hypothesis emerged regarding specific qualities of self-
related processing related to PCC activation. Of particular interest
in regard to previous associations with mind-wandering (e.g.,
Mason et al, 2007; Whitfield-Gabrieli et al., 2011), several med-
itators reported instances of mind wandering that did not elicit
PCC activation, or, likewise, reported using a strategy of mind

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Garrison et al.

Neurophenomenology of meditation using neurofeedback

wandering or self-related thinking in unsuccessful attempts to
activate the PCC:

Meditator 134 (run 12): For this meditation, now I just tried not
to push it at all, I just wanted to see what would happen with just
really resting, not visualizing anything, not using anything as a
tool, just opening up the space and resting, and I think towards
the middle I had some thoughts which I don't see on this graph
maybe because I just let them kind of flow by, but I noticed some
thoughts. But in general, it just felt a little bit more restful than the
last [run].

Meditator 141 (run 14): I was surprised that [the graph] was so
blue on that second part. I was observing a lot of what I was think-
ing, but I was thinking about a lot of things, for example, what I
had to do the rest of the day.

These and similar instances of mind wandering that did not
lead to PCC activation suggest that the PCC may be involved
in more subtle aspects of experience related to thinking rather
than just the thoughts themselves (e.g., Andrews-Hanna et al,
2010). Mind wandering or self-related thinking that does not
lead to PCC activation may be distinguished by a quality of
not being pushed, pulled, or lost in mental content, feelings,
or thoughts as they arise, described by meditators as "letting
things flow by" or "observing thinking." In contrast, mind wan-
dering or self-related thinking leading to PCC activation may
have a quality of reactivity to mental content or thoughts, such
as desire or aversion toward mental content, ruminative think-
ing, or "getting caught up in narrative." As the PCC becomes
activated during craving and emotion (Caravan et al., 2000;
Kober et al, 2008), further studies may also test whether the
particular qualities of self-related thinking leading to PCC acti-
vation influence how self-referential processing and mind wan-
dering lead to stress and disease (e.g., Killingsworth and Gilbert,
2010).

Another hypothesis emerged regarding specific qualities of
meditation practice related to PCC deactivation. Here, sev-
eral meditators made an explicit distinction between "effortful"
attempts to meditate associated with PCC activation, and "effort-
less" meditation associated with PCC deactivation:

Meditator 140 (run 11): The biggest thing I noticed was that the
more I relaxed and the less I did, the bluer [the graph] went . . . the
more I relaxed and stopped trying to do anything, the bluer [the
graph] went.

Meditator 123 (run 9): The red bars correspond to times when I
was trying to either force the experience or trying to think about,
thinking about stuff in general, thinking about making [the graph]
blue. And then when I could let it go, [the graph] turned blue.

These and similar instances distinguish between "effortful" and
"effortless" meditation, represented in the principle constructs of
"controlling" leading to PCC activation, and "effortless doing"
leading to PCC deactivation. These data suggest that "trying to
meditate" may be associated with PCC activation, whereas "not
trying" or effortless meditation maybe associated with PCC deac-
tivation. Such a distinction may be instructive for meditation
training.

Recently, Pearson et al. proposed that the PCC is involved in
signaling environmental change and shifts in behavior (Pearson
et al, 2011), whereby decreased PCC activity reflects operation
within a current cognitive set, and increased activity reflects a
change in environment (external or internal) and "promotes flexi-
bility, exploration, and renewed learning." Our data provide some
support for this, as we found consistent PCC deactivation asso-
ciated with concentration, staying within the framework of a
current cognitive set. The change in experience related to con-
centration may be when meditators force their concentration,
associated with PCC activation. If one were to interpret "effort-
ing" as related to inflexibility, rather than flexibility and learning,
our data do not provide support for Pearson's assertion that
increased PCC activity promotes flexibility. Future studies using
rtfMRI may directly test this.

Another distinction of interest emerged regarding meditators
reports of "sensory experience," which were associated with both
PCC activation and deactivation. Through the constant com-
parative method of GTM, we found that PCC activation was
associated with reports of being distracted by, reacting to, or
trying to control sensory objects (physical, visual, auditory, or
mental objects such as thoughts):

Meditator 141 (run 7): Especially when [the graph] started getting
really really red and I was like "Whoa that is a lot of red" and then
I noticed my mind was going "Whoa that is a lot of red."
Meditator 138 (run 14): I tried to bring my perception away from
the breath and more towards the visual and that brought [the
graph] back into the red at the end.

In contrast, PCC deactivation was associated with reports of con-
centration on, or awareness or observation of sensory experience:

Meditator 134 (run 13): Toward the middle I began to experience
a tingling through my body and so I was just kind of watching that
for a while.

Meditator 62 (run 10): I maintained primary awareness on the full
range of experience, including, just, awareness of the body and
various touch points, the breath moving throughout the body, the
sound being integrated into that sort of, sort of fuller awareness
while watching the colors with relative ease . . . body awareness.

These data suggest that sensory experience related to "distraction"
or "controlling" is associated with PCC activation, whereas sen-
sory experience related to "undistracted awareness" or "effortless
doing" is associated with PCC deactivation. This distinction was
in part task-related, as meditators were asked to use dynamic sen-
sory experience — both their breath and the feedback graph — as
the object of meditation. Meditators had to learn to be on task —
to pay attention to the breath and the graph — while meditating,
i.e., not being distracted by, interpreting, or controlling the breath
or the graph.

The current study drew meditators from a variety of contem-
plative traditions including Catholic contemplative, Theravada,
Zen, and Tibetan Buddhism. Despite this variation, consistent
hypotheses were derived that are in agreement with various tra-
ditional characterizations of the meditative state. For example, at
an advanced stage of practice, as one Theravada Buddhist teacher

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Garrison et al.

Neurophenomenology of meditation using neurofeedback

described, "There will arise knowledge perceiving evident bod-
ily and mental processes in continuous succession quite naturally,
as if borne onward of itself ... in the act of noticing, effort is
no longer required to keep formations before the mind or to
understand them" (Sayadaw, 1994). This consistency may extend
to instructions for Mahamudra training in Tibetan Buddhism
which include, "Do not pursue the past. Do not usher in the
future. Rest evenly with present awareness," and "Not meditating.
Not analyzing. Just place the mind in its natural state" (Karma
Wangchug Dorje, in Dunne, 201 1 ). Thus, the construct of effort-
less awareness seems to be evident in both traditional descriptions
of meditation practice, and in subjective reports of meditation
related to neural activity in adept meditators.

To further refine these hypotheses, additional neurophe-
nomenological studies can be conducted, driven by first-person
reports, whereby meditators are asked to distinguish (over ongo-
ing or successive real time feedback runs) between specific
aspects of their experience that are closely related but differ in
whether they elicit PCC activation or deactivation. Qualities of
"self-related thinking" or "trying/not-trying to meditate" can be
manipulated and reported upon by the individual, and further
emergent categories tested and refined across subjects. Further
studies will also investigate other regions of the default mode
network, as well as large-scale brain systems.

LIMITATIONS

An advantage of the approach was to include meditators, who
are highly trained at first-person methods such as introspection
(Fox et al., 2012) and who are able to gain access to different
aspects of their experience (Lutz and Thompson, 2003). However,
generalizability to novices or non-meditators may be limited
given that meditators have a prior context — their contemplative
tradition — within which to interpret both their meditation and
the neurofeedback. Just as contemplative training may enable
meditators to more carefully examine particular aspects of their
experience, training may also bias them to evaluate only certain
aspects of their experience. Moreover, meditators were presented
with Likert items after each run (e.g., how was your mental effort?)
that may have influenced introspection. Related to this, although
we followed the standards of GTM, it is possible that our coder
introduced interpretive bias, and a validation of the observed
relationships with newly acquired data across different coders
will improve reliability of our findings. Nevertheless, our find-
ings offer testable hypotheses for further study in meditators and
other groups such as novices, and clinical populations such as
stress.

In this study, demand characteristics may result from asking
meditators to look for correspondence between their experience
and the feedback graph. To minimize these, participants were
always asked to consider how the graph did or did not corre-
spond with their experience, and it was emphasized in training
that we were interested in how their own experience of meditation
corresponded with the graph. Related to this, first-person self-
reports may have been influenced by the feedback graph. During
steps 1, 2 in which meditators were provided offline feedback
after they had already described their experience, this potential
influence was overt, for example, "There's this one place where I

was getting lost, and I wonder if I'm wrong about where it was
[on the graph]? If it was closer to the beginning, then I can see
where there might be a place just a little ways in where [ the graph ]
goes back up? . . . I'm doubting myself where exactly that was."
Our real time feedback protocol was developed in an attempt to
minimize this potential confound (Garrison et al, 2013). Offline
feedback was provided in order to enable meditators to "dis-
cover" how their own experience related to the feedback graph.
For grounded theory, it was useful to have both first-person self-
reports uncontaminated by third-person data (steps 1, 2), as well
as self-reports enriched by evaluation related to real time neu-
rofeedback (steps 3, 4). Real time feedback also allowed us to
investigate the circular causality whereby (1) the ongoing first-
person experience (meditation) modulates the third-person data
(feedback graph), and (2) the content of the third-person data
(feedback) affects the moment-to-moment first-person experi-
ence, and so on.

Finally, other work using electroencephalography (EEC) has
shown that there is a fast on/off switch for task-related acti-
vation/deactivation of the PCC (Ossandon et al, 2011), sug-
gesting that PCC activity may represent lower-level processing
below that of conscious awareness, especially in individuals not
trained to be aware of subtle aspects of experience. In the cur-
rent study, the temporal resolution of rtfMRI did not allow us
to similarly examine PCC activity around the task of medita-
tion with this degree of temporal precision. Though efforting
arose as its own category separate from distraction in our anal-
ysis, in some cases, PCC activity may be related to distraction,
but perceived subjectively as efforting as meditators notice they
are distracted and try to counteract distraction. Additionally,
the PCC may be a marker of efforting but the actual effort to
redirect attention or counteract distraction is likely subserved
by other brain regions involved in cognitive control, for exam-
ple the dorsolateral prefrontal cortex (Brewer et al., 2011; Allen
et al., 2012). As the PCC was the only region that was ana-
lyzed here, future studies using EEC may be used to test these
hypotheses.

CONCLUSIONS

Using a neurophenomenological approach with grounded the-
ory analysis, we described and quantified several aspects of
the subjective experience of meditation related to PCC activ-
ity in adept meditators. "Undistracted awareness" and "effortless
doing" were associated with PCC deactivation, whereas "dis-
tracted awareness" and "controlling" were associated with PCC
activation. First-person reports of the subjective experience of
meditation provided new insights into more refined aspects of
meditation and self- related thinking associated with PCC activity,
such as the difference between meditation and "trying to med-
itate." These findings demonstrate the utility of our combined
approach to generate hypotheses about cognition for further
studies.

ACKNOWLEDGMENTS

We thank Aneesha Ahluwalia, Jonathan Chou, Nathan Fisher,
Nikos Melachrinos, Faye McKenna, Laura Reuter, and Rahil
Rojiani for transcription of self-reports; Hedy Sarofin and Karen

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Garrison et al.

Neurophenomenology of meditation using neurofeedback

Martin for their assistance with fMRI scanning; Willoughby
Britton, Christian Herwitz, Evan Thompson, Cliff Saron, and
Gaelle Desbordes for discussions about the theoretical approach;
Ginny Morgan and Joseph Goldstein for assistance with

meditation instructions; and Patrick Worhunsky for develop-
ment of the feedback display. This work was funded by private
donations from Jeffrey C. Walker, Austin Hearst, and the 1440
Foundation.

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Conflict of Interest Statement: The

authors declare that the research
was conducted in the absence of any
commercial or financial relationships
that could be construed as a potential
conflict of interest.

Received: 18 April 2013; paper pending
published: 24 May 2013; accepted: 17
July 2013; published online: 06 August
2013.

Citation: Garrison KA, Santoyo JF, Davis
JH, Thornhill TA IV, Kerr CE and Brewer
JA (2013) Effortless awareness: using real
time neurofeedback to investigate corre-
lates of posterior cingulate cortex activity
in meditators' self-report. Front. Hum.
Neurosci. 7:440. doi: 10.3389/fnhum.
2013.00440

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